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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669717/
Proper Citation: The HIV Positive Selection Mutation Database (RRID:SCR_007957)
Description: This is a dataset of clinical HIV sequences, including a method of decoding the evolutionary pathways by which HIV evolves drug resistance. "Fitness landscape" describing how HIV proteins can evolve, is shown as a kinetic network. Drug resistance is a major problem in the treatment of AIDS, due to the very high mutation rate of human immunodeficiency virus (HIV) and subsequent rapid development of resistance to new drugs. Identification of mutations associated with drug resistance is critical for both individualized treatment selection and new drug design. We have performed an automated mutation analysis of HIV Type 1 (HIV-1) protease and reverse transcriptase (RT) from approximately 50,000 AIDS patient plasma samples sequenced by Specialty Laboratories Inc. from 1999 to mid-2002. This dataset provides a nearly complete mutagenesis of HIV protease and enables the calculation of statistically significant Ka/Ks values for each individual amino acid mutation in protease and RT. Positive selection (i.e., Ka/Ks>1 indicating increased reproductive fitness) detected 19 of 23 known drug-resistant mutation positions in protease and 20 of 34 such positions in RT. We also discovered 163 new amino acid mutations in HIV protease and RT that are strong candidates for drug resistance or fitness. Our results match available independent data on protease mutations associated with specific drug treatments and mutations with positive reproductive fitness, with high statistical significance (the P values for the observed matches to occur by random chance are 1e-5.2 and 1e-16.6, respectively). Our data indicate that positive selection mapping is an analysis that can yield powerful insights from high-throughput sequencing of rapidly mutating pathogens. This database has been made possible by the generous contribution of HIV sequence chromatograms by Specialty Laboratories, Inc.
Synonyms: The HIV Positive Selection Mutation Database
Resource Type: database, data or information resource
Defining Citation: PMID:17108357
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The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant 2U24DK097771-09.
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